Deep Research

DeerFlow: Your Deep Research companion. Powered by search engines and AI to deliver instant insights and comprehensive analysis.

Get Started

Case Studies

See DeerFlow in action through replays.

DeerFlow helps you solve real research and automation challenges. With DeerFlow, you can build smart workflows using multi-agent collaboration and advanced search. The following cases show DeerFlow's flexibility and power in different scenarios.

How tall is Eiffel Tower compared to tallest building?

The research compares the heights and global significance of the Eiffel Tower and Burj Khalifa, and uses Python code to calculate the multiples.

Click to watch replay

What are the top trending repositories on GitHub?

The research utilized MCP services to identify the most popular GitHub repositories and documented them in detail using search engines.

Click to watch replay

Write an article about Nanjing's traditional dishes

The study vividly showcases Nanjing's famous dishes through rich content and imagery, uncovering their hidden histories and cultural significance.

Click to watch replay

How to decorate a small rental apartment?

The study provides readers with practical and straightforward methods for decorating apartments, accompanied by inspiring images.

Click to watch replay

Introduce the movie 'Léon: The Professional'

The research provides a comprehensive introduction to the movie 'Léon: The Professional', including its plot, characters, and themes.

Click to watch replay

How do you view the takeaway war in China? (in Chinese)

The research analyzes the intensifying competition between JD and Meituan, highlighting their strategies, technological innovations, and challenges.

Click to watch replay

Are ultra-processed foods linked to health?

The research examines the health risks of rising ultra-processed food consumption, urging more research on long-term effects and individual differences.

Click to watch replay

Write an article on "Would you insure your AI twin?"

The research explores the concept of insuring AI twins, highlighting their benefits, risks, ethical considerations, and the evolving regulatory.

Click to watch replay

DeerFlow is not just a research tool—it's a platform for building next-generation AI applications. By using DeerFlow, you can accelerate innovation, improve productivity, and ensure your solutions are powered by the latest advancements in AI and automation.

Multi-Agent Architecture

Experience the agent teamwork with our Supervisor + Handoffs design pattern.

DeerFlow's multi-agent architecture lets agents work together, share tasks, and solve complex problems. This makes DeerFlow ideal for automated research and advanced AI workflows, ensuring reliability and scalability.

Start

Coordinator

Planner

Reporter

Human Feedback

Research Team

Researcher

Coder

End

By leveraging DeerFlow's multi-agent system, you can unlock new levels of automation and intelligence, making DeerFlow the go-to solution for next-generation workflow orchestration and agent-based research.

Deep Research

Case Studies

How tall is Eiffel Tower compared to tallest building?

What are the top trending repositories on GitHub?

Write an article about Nanjing's traditional dishes

How to decorate a small rental apartment?

Introduce the movie &apos;Léon: The Professional&apos;

How do you view the takeaway war in China? (in Chinese)

Are ultra-processed foods linked to health?

Write an article on &quot;Would you insure your AI twin?&quot;

Multi-Agent Architecture

DeerFlow FAQ

What is DeerFlow?

Which language models does DeerFlow support?

How do I install and deploy DeerFlow?

What is the technology stack of DeerFlow?

How can I customize and extend DeerFlow workflows?

What is the license of DeerFlow? Can I use it commercially?

How can I get support or contribute to DeerFlow?

How does DeerFlow ensure data security and privacy?

How does DeerFlow compare to frameworks like LangChain or RAGFlow?

What is the future roadmap for DeerFlow?

What are the main use cases for DeerFlow?

What are some best practices for using DeerFlow?

How can I optimize the performance of DeerFlow workflows?

Can DeerFlow integrate with other AI platforms or tools?

How do I troubleshoot common errors in DeerFlow?

Are there any real-world user stories or case studies for DeerFlow?

What data sources does DeerFlow support?

Does DeerFlow provide an API for developers?

Can I customize the DeerFlow web UI?

What are the future trends for DeerFlow and agent-based research?

Introduce the movie 'Léon: The Professional'

Write an article on "Would you insure your AI twin?"